





from __future__ import annotations

import math





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> bool:




    """simple docstring"""




    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5							,     int(math.sqrt(_SCREAMING_SNAKE_CASE				) + 1				)							,     6				):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> list[int]:




    """simple docstring"""




    _A     =							str(_SCREAMING_SNAKE_CASE				)
    _A     =							[n]
    for i in range(1							,     len(_SCREAMING_SNAKE_CASE				)				):
        list_nums.append(int(str_num[i:]				)				)
        list_nums.append(int(str_num[:-i]				)				)
    return list_nums





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> bool:




    """simple docstring"""




    if len(str(_SCREAMING_SNAKE_CASE				)				) > 3:
        if not is_prime(int(str(_SCREAMING_SNAKE_CASE				)[-3:]				)				) or not is_prime(int(str(_SCREAMING_SNAKE_CASE				)[:3]				)				):
            return False
    return True





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE = 11				)							-> list[int]:




    """simple docstring"""




    _A     =							[]
    _A     =							13
    while len(_SCREAMING_SNAKE_CASE				) != count:
        if validate(_SCREAMING_SNAKE_CASE				):
            _A     =							list_truncated_nums(_SCREAMING_SNAKE_CASE				)
            if all(is_prime(_SCREAMING_SNAKE_CASE				) for i in list_nums				):
                list_truncated_primes.append(_SCREAMING_SNAKE_CASE				)
        num += 2
    return list_truncated_primes





def 				__lowerCAmelCase(       )							-> int:




    """simple docstring"""




    return sum(compute_truncated_primes(11				)				)


if __name__ == "__main__":
 print(f"{sum(compute_truncated_primes(11)) = }")









'''simple docstring'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_						:  List[Any]				  =						logging.get_logger(__name__)

UpperCAmelCase_						:  Any				  =						{
    'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}





class        lowercase__    (		_snake_case   ):





							'''simple docstring'''


							A_				: Dict       =    """gpt_bigcode"""
							A_				: str       =    ["""past_key_values"""]
							A_				: Tuple       =    {
							    """hidden_size""": """n_embd""",
							    """max_position_embeddings""": """n_positions""",
							    """num_attention_heads""": """n_head""",
							    """num_hidden_layers""": """n_layer""",
							}






							def __init__(       self       ,   __snake_case=5_0257       ,   __snake_case=1024       ,   __snake_case=768       ,   __snake_case=12       ,   __snake_case=12       ,   __snake_case=None       ,   __snake_case="gelu_pytorch_tanh"       ,   __snake_case=0.1       ,   __snake_case=0.1       ,   __snake_case=0.1       ,   __snake_case=1e-5       ,   __snake_case=0.02       ,   __snake_case=True       ,   __snake_case=True       ,   __snake_case=5_0256       ,   __snake_case=5_0256       ,   __snake_case=True       ,   __snake_case=True       ,   __snake_case=True       ,   **__snake_case       ,   ):
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= vocab_size
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= n_positions
											_SCREAMING_SNAKE_CASE					:			List[Any]							= n_embd
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= n_layer
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= n_head
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= n_inner
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= activation_function
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= resid_pdrop
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= embd_pdrop
											_SCREAMING_SNAKE_CASE					:			List[Any]							= attn_pdrop
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= layer_norm_epsilon
											_SCREAMING_SNAKE_CASE					:			Any							= initializer_range
											_SCREAMING_SNAKE_CASE					:			str							= scale_attn_weights
											_SCREAMING_SNAKE_CASE					:			Tuple							= use_cache
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= attention_softmax_in_fpaa
											_SCREAMING_SNAKE_CASE					:			List[Any]							= scale_attention_softmax_in_fpaa
											_SCREAMING_SNAKE_CASE					:			Any							= multi_query

											_SCREAMING_SNAKE_CASE					:			Optional[int]							= bos_token_id
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= eos_token_id

											super().__init__(bos_token_id=__snake_case       ,   eos_token_id=__snake_case       ,   **__snake_case    )




